Keywords: assembly, galaxy-interface, introduction, microbiome, proteomics, single-cell, statistics, variant-analysis

Learning objectives:

• Assess long reads FASTQ quality using Nanoplot and PycoQC
• Assess short reads FASTQ quality using FASTQE 🧬😎 and FastQC
• Become comfortable converting text-based files in a variety of ways.
• Connect different parts of the Research Object using identifiers
• Construct an RO-Crate by hand using JSON
• Describe each part of the Research Object
• Explain what is a BAM file and what it contains
• Familiarize yourself with data manipulation tools in Galaxy
• Familiarize yourself with the basics of Galaxy
• Gain understanding on navigating and manipulating histories
• Generate a workflow test using Planemo
• Learn about how Galaxy handles NGS data using Illumina data derived from patients infected with SARS-CoV-2
• Learn basic JSON-LD to create FAIR metadata
• Learn how histories work
• Learn how to create a workflow
• Learn how to extract and run a workflow
• Learn how to obtain data from external sources
• Learn how to run tools
• Learn how to share a history
• Learn how to share your work
• Learn how to upload a file
• Learn how to use a tool
• Learn how to view histories
• Learn how to view results
• Perform basic text manipulation tasks in Galaxy
• Perform quality correction with Cutadapt (short reads)
• Process single-end and paired-end data
• Reason about the expected outcome of tools
• Run a tool to map reads to a reference genome
• Summarise quality metrics MultiQC
• Understand and master dataset collections
• Understand how testing can be automated with GitHub Actions
• Understand most common types of NGS-related datatypes
• Use genome browser to understand your data

Organizer: Armin Dadras (https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/), Delphine Lariviere (https://training.galaxyproject.org/training-material/hall-of-fame/delphine-l/), Diana Chiang Jurado (https://training.galaxyproject.org/training-material/hall-of-fame/dianichj/), Natalie Whitaker-Allen (https://training.galaxyproject.org/training-material/hall-of-fame/natalie-wa/), Saskia Hiltemann (https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/), Scott Cain (https://training.galaxyproject.org/training-material/hall-of-fame/scottcain/), Teresa Müller (https://training.galaxyproject.org/training-material/hall-of-fame/teresa-m/)

Event types:

• Workshops and courses

Sponsors: ABRomics, ELIXIR Europe, Institut Français de Bioinformatique, Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg, de.NBI

Scientific topics: Mapping